Practical Artificial Intelligence PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Practical Artificial Intelligence PDF full book. Access full book title Practical Artificial Intelligence by Arnaldo Pérez Castaño. Download full books in PDF and EPUB format.

Practical Artificial Intelligence

Practical Artificial Intelligence PDF Author: Arnaldo Pérez Castaño
Publisher: Apress
ISBN: 1484233573
Category : Computers
Languages : en
Pages : 690

Get Book

Book Description
Discover how all levels Artificial Intelligence (AI) can be present in the most unimaginable scenarios of ordinary lives. This book explores subjects such as neural networks, agents, multi agent systems, supervised learning, and unsupervised learning. These and other topics will be addressed with real world examples, so you can learn fundamental concepts with AI solutions and apply them to your own projects. People tend to talk about AI as something mystical and unrelated to their ordinary life. Practical Artificial Intelligence provides simple explanations and hands on instructions. Rather than focusing on theory and overly scientific language, this book will enable practitioners of all levels to not only learn about AI but implement its practical uses. What You’ll Learn Understand agents and multi agents and how they are incorporated Relate machine learning to real-world problems and see what it means to you Apply supervised and unsupervised learning techniques and methods in the real world Implement reinforcement learning, game programming, simulation, and neural networks Who This Book Is For Computer science students, professionals, and hobbyists interested in AI and its applications.

Practical Artificial Intelligence

Practical Artificial Intelligence PDF Author: Arnaldo Pérez Castaño
Publisher: Apress
ISBN: 1484233573
Category : Computers
Languages : en
Pages : 690

View

Book Description
Discover how all levels Artificial Intelligence (AI) can be present in the most unimaginable scenarios of ordinary lives. This book explores subjects such as neural networks, agents, multi agent systems, supervised learning, and unsupervised learning. These and other topics will be addressed with real world examples, so you can learn fundamental concepts with AI solutions and apply them to your own projects. People tend to talk about AI as something mystical and unrelated to their ordinary life. Practical Artificial Intelligence provides simple explanations and hands on instructions. Rather than focusing on theory and overly scientific language, this book will enable practitioners of all levels to not only learn about AI but implement its practical uses. What You’ll Learn Understand agents and multi agents and how they are incorporated Relate machine learning to real-world problems and see what it means to you Apply supervised and unsupervised learning techniques and methods in the real world Implement reinforcement learning, game programming, simulation, and neural networks Who This Book Is For Computer science students, professionals, and hobbyists interested in AI and its applications.

Practical Artificial Intelligence with Swift

Practical Artificial Intelligence with Swift PDF Author: Mars Geldard
Publisher: "O'Reilly Media, Inc."
ISBN: 1492044768
Category : Computers
Languages : en
Pages : 526

View

Book Description
Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you’ll learn how to build features that use powerful AI features to identify images, make predictions, generate content, recommend things, and more. AI is increasingly essential for every developer—and you don’t need to be a data scientist or mathematician to take advantage of it in your apps. Explore Swift-based AI and ML techniques for building applications. Learn where and how AI-driven features make sense. Inspect tools such as Apple’s Python-powered Turi Create and Google’s Swift for TensorFlow to train and build models. I: Fundamentals and Tools—Learn AI basics, our task-based approach, and discover how to build or find a dataset. II: Task Based AI—Build vision, audio, text, motion, and augmentation-related features; learn how to convert preexisting models. III: Beyond—Discover the theory behind task-based practice, explore AI and ML methods, and learn how you can build it all from scratch... if you want to

Practical Artificial Intelligence and Blockchain

Practical Artificial Intelligence and Blockchain PDF Author: Ganesh Prasad Kumble
Publisher: Packt Publishing Ltd
ISBN: 183882507X
Category : Computers
Languages : en
Pages : 290

View

Book Description
Learn how to use AI and blockchain to build decentralized intelligent applications (DIApps) that overcome real-world challenges Key Features Understand the fundamental concepts for converging artificial intelligence and blockchain Apply your learnings to build apps using machine learning with Ethereum, IPFS, and MoiBit Get well-versed with the AI-blockchain ecosystem to develop your own DIApps Book Description AI and blockchain are two emerging technologies catalyzing the pace of enterprise innovation. With this book, you’ll understand both technologies and converge them to solve real-world challenges. This AI blockchain book is divided into three sections. The first section covers the fundamentals of blockchain, AI, and affiliated technologies, where you’ll learn to differentiate between the various implementations of blockchains and AI with the help of examples. The second section takes you through domain-specific applications of AI and blockchain. You’ll understand the basics of decentralized databases and file systems and connect the dots between AI and blockchain before exploring products and solutions that use them together. You’ll then discover applications of AI techniques in crypto trading. In the third section, you’ll be introduced to the DIApp design pattern and compare it with the DApp design pattern. The book also highlights unique aspects of SDLC (software development lifecycle) when building a DIApp, shows you how to implement a sample contact tracing application, and delves into the future of AI with blockchain. By the end of this book, you’ll have developed the skills you need to converge AI and blockchain technologies to build smart solutions using the DIApp design pattern. What you will learn Get well-versed in blockchain basics and AI methodologies Understand the significance of data collection and cleaning in AI modeling Discover the application of analytics in cryptocurrency trading Get to grips with open, permissioned, and private blockchains Explore the DIApp design pattern and its merit in digital solutions Find out how LSTM and ARIMA can be applied in crypto trading Use the DIApp design pattern to build a sample contact tracing application Get started with building your own DIApps across various domains Who this book is for This book is for blockchain and AI architects, developers, data scientists, data engineers, and evangelists who want to harness the power of artificial intelligence in blockchain applications. If you are looking for a blend of theoretical and practical use cases to understand how to implement smart cognitive insights into blockchain solutions, this book is what you need! Knowledge of machine learning and blockchain concepts is required.

Generatives Deep Learning

Generatives Deep Learning PDF Author: David Foster
Publisher:
ISBN:
Category :
Languages : de
Pages : 310

View

Book Description
Generative Modelle haben sich zu einem der spannendsten Themenbereiche der Künstlichen Intelligenz entwickelt: Mit generativem Deep Learning ist es inzwischen möglich, einer Maschine das Malen, Schreiben oder auch das Komponieren von Musik beizubringen - kreative Fähigkeiten, die bisher dem Menschen vorbehalten waren. Mit diesem praxisnahen Buch können Data Scientists einige der eindrucksvollsten generativen Deep-Learning-Modelle nachbilden wie z.B. Generative Adversarial Networks (GANs), Variational Autoencoder (VAEs), Encoder-Decoder- sowie World-Modelle. David Foster veranschaulicht die Funktionsweise jeder Methode, beginnend mit den Grundlagen des Deep Learning mit Keras, bevor er zu einigen der modernsten Algorithmen auf diesem Gebiet vorstößt. Die zahlreichen praktischen Beispiele und Tipps helfen dem Leser herauszufinden, wie seine Modelle noch effizienter lernen und noch kreativer werden können.

Practical Artificial Intelligence

Practical Artificial Intelligence PDF Author: Christian Finlay
Publisher: Independently Published
ISBN: 9781723894374
Category :
Languages : en
Pages : 436

View

Book Description
This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated edition also includes new material on deep learning. Topics and features: presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, highlighted examples, definitions, theorems; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, etc. Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material.

Practical Machine Learning in R

Practical Machine Learning in R PDF Author: Fred Nwanganga
Publisher: John Wiley & Sons
ISBN: 1119591511
Category : Computers
Languages : en
Pages : 464

View

Book Description
Guides professionals and students through the rapidly growing field of machine learning with hands-on examples in the popular R programming language Machine learning—a branch of Artificial Intelligence (AI) which enables computers to improve their results and learn new approaches without explicit instructions—allows organizations to reveal patterns in their data and incorporate predictive analytics into their decision-making process. Practical Machine Learning in R provides a hands-on approach to solving business problems with intelligent, self-learning computer algorithms. Bestselling author and data analytics experts Fred Nwanganga and Mike Chapple explain what machine learning is, demonstrate its organizational benefits, and provide hands-on examples created in the R programming language. A perfect guide for professional self-taught learners or students in an introductory machine learning course, this reader-friendly book illustrates the numerous real-world business uses of machine learning approaches. Clear and detailed chapters cover data wrangling, R programming with the popular RStudio tool, classification and regression techniques, performance evaluation, and more. Explores data management techniques, including data collection, exploration and dimensionality reduction Covers unsupervised learning, where readers identify and summarize patterns using approaches such as apriori, eclat and clustering Describes the principles behind the Nearest Neighbor, Decision Tree and Naive Bayes classification techniques Explains how to evaluate and choose the right model, as well as how to improve model performance using ensemble methods such as Random Forest and XGBoost Practical Machine Learning in R is a must-have guide for business analysts, data scientists, and other professionals interested in leveraging the power of AI to solve business problems, as well as students and independent learners seeking to enter the field.

Practical AI for Healthcare Professionals

Practical AI for Healthcare Professionals PDF Author: Abhinav Suri
Publisher: Apress
ISBN: 9781484277799
Category : Computers
Languages : en
Pages : 254

View

Book Description
Practical AI for Healthcare Professionals Artificial Intelligence (AI) is a buzzword in the healthcare sphere today. However, notions of what AI actually is and how it works are often not discussed. Furthermore, information on AI implementation is often tailored towards seasoned programmers rather than the healthcare professional/beginner coder. This book gives an introduction to practical AI in the medical sphere, focusing on real-life clinical problems, how to solve them with actual code, and how to evaluate the efficacy of those solutions. You’ll start by learning how to diagnose problems as ones that can and cannot be solved with AI. You’ll then learn the basics of computer science algorithms, neural networks, and when each should be applied. Then you’ll tackle the essential parts of basic Python programming relevant to data processing and making AI programs. The Tensorflow/Keras library along with Numpy and Scikit-Learn are covered as well. Once you’ve mastered those basic computer science and programming concepts, you can dive into projects with code, implementation details, and explanations. These projects give you the chance to explore using machine learning algorithms for issues such as predicting the probability of hospital admission from emergency room triage and patient demographic data. We will then use deep learning to determine whether patients have pneumonia using chest X-Ray images. The topics covered in this book not only encompass areas of the medical field where AI is already playing a major role, but also are engineered to cover as much as possible of AI that is relevant to medical diagnostics. Along the way, readers can expect to learn data processing, how to conceptualize problems that can be solved by AI, and how to program solutions to those problems. Physicians and other healthcare professionals who can master these skills will be able to lead AI-based research and diagnostic tool development, ultimately benefiting countless patients.

A Practical Guide to Artificial Intelligence and Data Analytics

A Practical Guide to Artificial Intelligence and Data Analytics PDF Author: Rayan Wali
Publisher: Rayan Wali
ISBN:
Category : Computers
Languages : en
Pages : 512

View

Book Description
Whether you are looking to prepare for AI/ML/Data Science job interviews or you are a beginner in the field of Data Science and AI, this book is designed for engineers and AI enthusiasts like you at all skill levels. Taking a different approach from a traditional textbook style of instruction, A Practical Guide to AI and Data Analytics touches on all of the fundamental topics you will need to understand deeper into machine learning and artificial intelligence research, literature, and practical applications with its three parts: Part I: Concept Instruction Part II: 10 Full-Length Case Studies Part III: A Full-Length Assessment With an illustrative approach to instruction, worked examples, and case studies, this easy-to-understand book simplifies many of the AI and Data Analytics key concepts, leading to an improvement of AI/ML system design skills.

PRACTICAL ARTIFICIAL INTELLIGENCE PROJECTS

PRACTICAL ARTIFICIAL INTELLIGENCE PROJECTS PDF Author: TARRY. SINGH
Publisher:
ISBN: 9781788830027
Category :
Languages : en
Pages :

View

Book Description


The Artificial Intelligence Imperative: A Practical Roadmap for Business

The Artificial Intelligence Imperative: A Practical Roadmap for Business PDF Author: Anastassia Lauterbach
Publisher: ABC-CLIO
ISBN: 1440859957
Category : Computers
Languages : en
Pages : 290

View

Book Description
This practical guide to artificial intelligence and its impact on industry dispels common myths and calls for cross-sector, collaborative leadership for the responsible design and embedding of AI in the daily work of businesses and oversight by boards. • Provides a strategic framework for corporate boards and executive leadership teams to remain competitive in the age of AI • Offers practical and clear advice on AI and machine learning, introducing technical concepts and translating research trends into practical applications while simultaneously incorporating critical governance, ethics, sustainability, and risk considerations • Provides traditional businesses and their boards with practical questions to ask their teams, suppliers, and technology partners and offers guidance on market trends and players to which to pay attention